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Jessica Grogan
Theoretical Computer Science Ph.D. student at SUNY Buffalo. I have many interests, including logic, theoretical computer science, and machine learning.
My advisor is Atri Rudra.
CV (November 2024)
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Connect
Twitter
LinkedIn
GitHub
Email: [email protected]
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Publications
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Monarch Mixer: A Simple Sub-Quadratic GEMM-Based Architecture
Daniel Y. Fu, Simran Arora*, Jessica Grogan*, Isys Johnson*, Sabri Eyuboglu*, Armin W. Thomas*, Benjamin F. Spector, Michael Poli, Atri Rudra, Christopher Ré
In NeurIPS: 27th Conference on Neural Information Processing Systems , Dec. 2023. Oral presentation
[Paper]
[Code]
[Blog Post]
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Monarch: Expressive Structured Matrices for Efficient and Accurate Training
Tri Dao, Beidi Chen, Nimit Sohoni, Arjun Desai, Michael Poli, Jessica Grogan, Alexander Liu, Aniruddh Rao, Atri Rudra, Christopher Ré.
In ICML: 39th International Conference on Machine Learning, July 2022. Outstanding Paper Runner-up
[Paper]
[Code]
[Poster]
Outstanding Poster Award at the
EfficientML Bay Area meetup
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